​Multiphysics Modeling Scientist​

Job Duties

• Develop continuum-scale reactor models for dry inorganic powder synthesis, coupling heat transfer, gas flow, mass transport, and reaction kinetics to guide reactor conditions and experimental planning.
• Upgrade existing COMSOL-based implementations for thermal abuse modeling of ASSB cells.
• Develop and validate mathematical models (both fundamental physics-based and data-driven) to predict thermal, mechanical, and electrochemical behavior of ASSB materials, sub-assemblies, and finished cells.
• Work with subject matter experts to develop experimental plans to isolate and quantify key model parameters, while producing minimal solvers that can be used by scientists/engineers.
• Collaborate with subject matter experts to refine and continually validate modeling approaches, while employing best-practice workflows (i.e., mesh sensitivity analysis, ablation testing, unit testing, parameter sensitivity quantification).
• Clearly explain to internal stakeholders the uncertainty in modeling predictions and write documentation on proposed upgrades that could be used to improve certainty.
• Collaborate with data scientists on strategies to accelerate multiphysics modeling solvers and on strategies to guide virtual experiment prioritization (e.g., Bayesian approaches).
• Collaborate with atomic-scale and coarse-grained modeling team members to translate their outputs into continuum-scale model inputs, assumptions, parameters, and validation targets.

Qualifications/Requirements

• Master’s or Ph.D. in Computational Chemistry, Materials Engineering, Chemical Engineering or a related Electrochemical discipline.
• 2+ years of professional experience using commercial software to develop multiphysics models of lithium-ion batteries.
• A deep understanding of electrochemistry, preferably with at least some experience in battery systems.
• Proficiency with Python and common data science libraries such as Pandas, NumPy, and SciPy.
• Strong analytical and statistical problem-solving skills, having specific experience with configuring solvers for regression and parametrization tasks.
• Experience working with COMSOL is necessary. Experience working in Ansys, work with PyBaMM, and general python knowledge are all a strong plus.
• Previous experience building 1D PDE/ODE models from first principles and manually implementing them is a strong plus (e.g., Numpy implementation for Gummel iteration, Newton iteration, segregated solver).
• The ability to formulate coupled multiphysics models from first principles, including governing equations, assumptions, constitutive relationships, source terms, and boundary/initial conditions, prior to software implementation is a must.
• Familiarity with agentic code development concepts and the limitations of LLMs is a plus.
• The candidate should be someone who stays up to date on the latest continuum-scale modeling approaches.
• Rapid learner and a self-motivated individual who takes ownership in a collaborative start-up environment.
• Excellent communication, negotiation, and organizational skills with strong attention to detail.